Search results for: V. Vaidehi

Authors: Abdullah Mohamed, Raipat Vaidehi

Abstract:

With increasing immigration to urban areas, every city is experiencing shortage of housing. Vertical habitats are the only solution to this problem, it is hence important to make sure that these habitats are environmentally, socially and economically sustainable. A lot of work on vertical habitats has already been carried out in terms of environmental and economic sustainability, hence this research aims to study the aspects of social sustainability of the vertical habitats. It being the least studied topic, opens many reals of novelty and uniqueness. In this Research, user perception survey and various mapping methods have been used to study the social sustainability of the existing vertical habitats in the selected cities. The various aspects that can be used to define social sustainability of any place include; safety, equity, accessibility, legibility, imagibility, readability, memorability and ease of movement. This research would help to evolve new strategies in form of design and/or guidelines to make the existing vertical habitats socially sustainable.

Keywords: user lifestyle, user perception, social sustainability, vertical habitats

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Authors: Vaidehi Iyer, Konstantin Borozdin

Abstract:

Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: A: Annis Fathima, V. Vaidehi, S. Ajitha

Abstract:

Face recognition system finds many applications in surveillance and human computer interaction systems. As the applications using face recognition systems are of much importance and demand more accuracy, more robustness in the face recognition system is expected with less computation time. In this paper, a hybrid approach for face recognition combining Gabor Wavelet and Linear Discriminant Analysis (HGWLDA) is proposed. The normalized input grayscale image is approximated and reduced in dimension to lower the processing overhead for Gabor filters. This image is convolved with bank of Gabor filters with varying scales and orientations. LDA, a subspace analysis techniques are used to reduce the intra-class space and maximize the inter-class space. The techniques used are 2-dimensional Linear Discriminant Analysis (2D-LDA), 2-dimensional bidirectional LDA ((2D)2LDA), Weighted 2-dimensional bidirectional Linear Discriminant Analysis (Wt (2D)2 LDA). LDA reduces the feature dimension by extracting the features with greater variance. k-Nearest Neighbour (k-NN) classifier is used to classify and recognize the test image by comparing its feature with each of the training set features. The HGWLDA approach is robust against illumination conditions as the Gabor features are illumination invariant. This approach also aims at a better recognition rate using less number of features for varying expressions. The performance of the proposed HGWLDA approaches is evaluated using AT&T database, MIT-India face database and faces94 database. It is found that the proposed HGWLDA approach provides better results than the existing Gabor approach.

Keywords: face recognition, Gabor wavelet, LDA, k-NN classifier

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

Abstract:

Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Paresh Patel, Priya Patel, Vaidehi Sorathiya, Navin Sheth

Abstract:

The aim of present work was to fabricate Salmeterol Xinafoate (SX) metered dose inhaler (MDI) for asthma and to evaluate the SX loaded solid lipid nanoparticles (SLNs) for pulmonary delivery. Solid lipid nanoparticles can be used to deliver particles to the lungs via MDI. A modified solvent emulsification diffusion technique was used to prepare Salmeterol Xinafoate loaded solid lipid nanoparticles by using compritol 888 ATO as lipid, tween 80 as surfactant, D-mannitol as cryoprotecting agent and L-leucine was used to improve aerosolization behaviour. Box-Behnken design was applied with 17 runs. 3-D surface response plots and contour plots were drawn and optimized formulation was selected based on minimum particle size and maximum % EE. % yield, in vitro diffusion study, scanning electron microscopy, X-ray diffraction, DSC, FTIR also characterized. Particle size, zeta potential analyzed by Zetatrac particle size analyzer and aerodynamic properties was carried out by cascade impactor. Pre convulsion time was examined for control group, treatment group and compare with marketed group. MDI was evaluated for leakage test, flammability test, spray test and content per puff. By experimental design, particle size and % EE found to be in range between 119-337 nm and 62.04-76.77% by solvent emulsification diffusion technique. Morphologically, particles have spherical shape and uniform distribution. DSC & FTIR study showed that no interaction between drug and excipients. Zeta potential shows good stability of SLNs. % respirable fraction found to be 52.78% indicating reach to the deep part of lung such as alveoli. Animal study showed that fabricated MDI protect the lungs against histamine induced bronchospasm in guinea pigs. MDI showed sphericity of particle in spray pattern, 96.34% content per puff and non-flammable. SLNs prepared by Solvent emulsification diffusion technique provide desirable size for deposition into the alveoli. This delivery platform opens up a wide range of treatment application of pulmonary disease like asthma via solid lipid nanoparticles.

Keywords: salmeterol xinafoate, solid lipid nanoparticles, box-behnken design, solvent emulsification diffusion technique, pulmonary delivery

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Authors: Vaidehi Raipat

Abstract:

A city is an expression of coexistence between its users and built environment. The way in which its spaces are animated signify the quality of this coexistence. Urban sustainability is the ability of a city to respond efficiently towards its people, culture, environment, visual image, history, visions and identity. The quality of built environment determines the quality of our lifestyles, but poor ability of the built environment to adapt and sustain itself through the changes leads to degradation of cities. Ranchi was created in November 2000, as the capital of the newly formed state Jharkhand, located on eastern side of India. Before this Ranchi was known as summer capital of Bihar and was a little larger than a town in terms of development. But since then it has been vigorously expanding in size, infrastructure as well as population. This sudden expansion has created a stress on existing built environment. The large forest covers, agricultural land, diverse culture and pleasant climatic conditions have degraded and decreased to a large extent. Narrow roads and old buildings are unable to bear the load of the changing requirements, fast improving technology and growing population. The built environment has hence been rendered unsustainable and unadaptable through fastidious changes of present era. Some of the common hazards that can be easily spotted in the built environment are half-finished built forms, pedestrians and vehicles moving on the same part of the road. Unpaved areas on street edges. Over-sized, bright and randomly placed hoardings. Negligible trees or green spaces. The old buildings have been poorly maintained and the new ones are being constructed over them. Roads are too narrow to cater to the increasing traffic, both pedestrian and vehicular. The streets have a large variety of activities taking place on them, but haphazardly. Trees are being cut down for road widening and new constructions. There is no space for greenery in the commercial as well as old residential areas. The old infrastructure is deteriorating because of poor maintenance and the economic limitations. Pseudo understanding of functionality as well as aesthetics drive the new infrastructure. It is hence necessary to evaluate the extent of sustainability of existing built environment of the city and create or regenerate the existing built environment into a more sustainable and adaptable one. For this purpose, research titled “Sustainability of the Built Environment of Ranchi District” has been carried out. In this research the condition of the built environment of Ranchi are explored so as to figure out the problems and shortcomings existing in the city and provide for design strategies that can make the existing built-environment sustainable. The built environment of Ranchi that include its outdoor spaces like streets, parks, other open areas, its built forms as well as its users, has been analyzed in terms of various urban design parameters. Based on which strategies have been suggested to make the city environmentally, socially, culturally and economically sustainable.

Keywords: adaptable, built-environment, sustainability, urban

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